Harmonization of maternal balanced energy-protein supplementation studies for individual participant data (IPD) meta-analyses - finding and creating similarities in variables and data collection

Alison D. Gernand, Department of Nutritional Sciences, The Pennsylvania State University, 110 Chandlee Lab, University Park, PA, 16802, USA. adg14@psu.edu.
Kelly Gallagher, Department of Nutritional Sciences, The Pennsylvania State University, 110 Chandlee Lab, University Park, PA, 16802, USA.
Nita Bhandari, Centre for Health Research and Development Society for Applied Studies, New Delhi, India.
Patrick Kolsteren, Department of Food Technology, Safety and Health, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
Anne Cc Lee, Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Yasir Shafiq, VITAL Pakistan Trust, Karachi, Pakistan.
Sunita Taneja, Centre for Health Research and Development Society for Applied Studies, New Delhi, India.
James M. Tielsch, Department of Global Health, The George Washington University Milken Institute School of Public Health, Washington, D.C, USA.
Firehiwot Workneh Abate, Department of Epidemiology and Biostatistics, Addis Continental Institute of Public Health, Addis Adaba, Ethiopia.
Estifanos Baye, Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Yemane Berhane, Department of Epidemiology and Biostatistics, Addis Continental Institute of Public Health, Addis Adaba, Ethiopia.
Ranadip Chowdhury, Centre for Health Research and Development Society for Applied Studies, New Delhi, India.
Trenton Dailey-Chwalibóg, Department of Food Technology, Safety and Health, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
Brenda de Kok, Department of Food Technology, Safety and Health, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
Neeta Dhabhai, Centre for Health Research and Development Society for Applied Studies, New Delhi, India.
Fyezah Jehan, Department of Pediatrics and Child Health, Aga Khan University, Karachi, Pakistan.
Yunhee Kang, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Joanne Katz, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Subarna Khatry, Nepal Nutrition Intervention Project-Sarlahi, Lalitpur, Nepal.
Carl Lachat, Department of Food Technology, Safety and Health, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
Sarmila Mazumder, Centre for Health Research and Development Society for Applied Studies, New Delhi, India.
Ameer Muhammad, VITAL Pakistan Trust, Karachi, Pakistan.
Muhammad Imran Nisar, Department of Pediatrics and Child Health, Aga Khan University, Karachi, Pakistan.
Sitanshi Sharma, Centre for Health Research and Development Society for Applied Studies, New Delhi, India.
Leigh A. Martin, Department of Nutritional Sciences, The Pennsylvania State University, 110 Chandlee Lab, University Park, PA, 16802, USA.
Ravi Prakash Upadhyay, Centre for Health Research and Development Society for Applied Studies, New Delhi, India.
Parul Christian, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

Document Type

Journal Article

Publication Date

2-11-2023

Journal

BMC pregnancy and childbirth

Volume

23

Issue

1

DOI

10.1186/s12884-023-05366-2

Keywords

Antenatal; Balanced energy-protein supplementation; IPD meta-analysis; Lactation; Maternal and neonatal outcomes; Micronutrients; Preconception; Pregnancy

Abstract

BACKGROUND: Public health and clinical recommendations are established from systematic reviews and retrospective meta-analyses combining effect sizes, traditionally, from aggregate data and more recently, using individual participant data (IPD) of published studies. However, trials often have outcomes and other meta-data that are not defined and collected in a standardized way, making meta-analysis problematic. IPD meta-analysis can only partially fix the limitations of traditional, retrospective, aggregate meta-analysis; prospective meta-analysis further reduces the problems. METHODS: We developed an initiative including seven clinical intervention studies of balanced energy-protein (BEP) supplementation during pregnancy and/or lactation that are being conducted (or recently concluded) in Burkina Faso, Ethiopia, India, Nepal, and Pakistan to test the effect of BEP on infant and maternal outcomes. These studies were commissioned after an expert consultation that designed recommendations for a BEP product for use among pregnant and lactating women in low- and middle-income countries. The initiative goal is to harmonize variables across studies to facilitate IPD meta-analyses on closely aligned data, commonly called prospective meta-analysis. Our objective here is to describe the process of harmonizing variable definitions and prioritizing research questions. A two-day workshop of investigators, content experts, and advisors was held in February 2020 and harmonization activities continued thereafter. Efforts included a range of activities from examining protocols and data collection plans to discussing best practices within field constraints. Prior to harmonization, there were many similar outcomes and variables across studies, such as newborn anthropometry, gestational age, and stillbirth, however, definitions and protocols differed. As well, some measurements were being conducted in several but not all studies, such as food insecurity. Through the harmonization process, we came to consensus on important shared variables, particularly outcomes, added new measurements, and improved protocols across studies. DISCUSSION: We have fostered extensive communication between investigators from different studies, and importantly, created a large set of harmonized variable definitions within a prospective meta-analysis framework. We expect this initiative will improve reporting within each study in addition to providing opportunities for a series of IPD meta-analyses.

Department

Global Health

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